CN116074853A - Deployment optimization method for monitoring network of variable water area - Google Patents
Deployment optimization method for monitoring network of variable water area Download PDFInfo
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Abstract
The invention discloses a deployment optimization method for a monitoring network of a variable water area. The sensing nodes are combined with the water area state to adjust working conditions, and corresponding monitoring states are adopted to conduct sensing monitoring under different water area states, so that the purpose of energy saving and optimization is achieved. In addition, the method forms a mobile monitoring network by moving and adjusting the detection node and the monitoring equipment according to the expected position. The monitoring device adjusts the real-time position to the reference position by comparing the difference between the reference position and the real-time position. The detection node performs movement adjustment by comparing the first neighbor node set with the second neighbor node set and utilizing the sensing radius of the detection node, and the energy-saving optimization of the mobile monitoring network is realized by constructing the deployment optimization method.
Description
Technical Field
The invention relates to a real-time monitoring system of a local water area, in particular to a deployment optimization method for a monitoring network of a variable water area.
Background
The monitoring network arranged in the water area can be used for observing various parameters on the water surface and under water, and can be widely applied to the fields of weather, fishery and the like. Large waters are susceptible to tides, weather, especially in freshwater lakes and offshore areas. The water area data inevitably offsets the monitoring network, so that the data of part of the cultivation area are repeated, the data of part of the cultivation area are lost, the energy consumption loss of the sensing network nodes is increased, and even the equipment needs to be replaced in advance. Different from the field of fine industry, the aquaculture is difficult to replace monitoring equipment frequently.
Related technologies in the similar field, such as an energy-saving method for an IPv6 wireless sensor network disclosed in CN102695249A, optimize the working condition of a wireless sensor network node by designing a node directional dormancy mechanism. As another example, CN111885533B discloses a way to reduce the working energy consumption of nodes by reducing signal transmission hops through sensor network node clustering. However, in the practical use environment, in order to reduce the cost, too many monitoring objects are not needed, and the sensor network nodes are relatively fixed. The network topology between the nodes is relatively single and solidified, and the problem of energy consumption loss of the sensor network is difficult to solve from the viewpoint of the working property of the nodes. Therefore, there is a need in the art for further improvements in how to optimize the deployment of a monitoring network for variable waters.
Disclosure of Invention
Aiming at the problems, the invention provides a deployment optimization method for a monitoring network of a variable water area. According to the method, the monitoring equipment and the detection nodes can move according to the position change, so that the coverage rate of the water area sensing network is kept at the optimal level, and the loss of energy consumption is reduced. In addition, the working condition of the detection node is adjusted according to the water area states under different conditions, and the detection node works at a lower detection frequency in a tide state, so that the effect of saving energy consumption is achieved.
The aim of the invention can be achieved by the following technical means:
a deployment optimization method for a monitoring network of a variable water area, comprising the steps of:
step 1: arranging a plurality of monitoring devices in a water area monitoring area, wherein any one monitoring device is connected with only one underwater detection node through a communication cable;
step 2: the monitoring equipment broadcasts a first sensing signal, and the detecting node senses the information of the peripheral neighbor nodes, generates a first neighbor node set and reports the first neighbor node set to the server through the monitoring equipment;
step 3: the server broadcasts a first detection signal, the monitoring equipment reports the position information, and the moving step length d is set x The server generates a reference position set based on the reference position reported by the monitoring equipment;
step 4: in a monitoring period, the monitoring equipment periodically acquires water area data m i I=1, 2,3 …, and generates a water area data set m= { M 1 ,m 2 ,m 3 …m i }；
Step 5: the monitoring device calculates the water area variation based on the water area data set M
=m i -m 1 If->
Or (b)
The detection node enters a first monitoring state, if +.>
The detection node enters a second monitoring state, wherein +_>
The absolute value of the floating number is changed for the water area; />
Step 6: the server broadcasts a second detection signal, the monitoring equipment reports the position information, and the moving step length d is set y The server is based onThe real-time position reported by the monitoring equipment generates a real-time position set;
step 7: the server generates first vector data according to the real-time position set and the reference position set, and the monitoring equipment moves to a first expected position based on the first vector data;
step 8: the monitoring equipment broadcasts a second sensing signal, and the detecting node senses the information of the peripheral neighbor nodes, generates a second neighbor node set and reports the second neighbor node set to the server through the monitoring equipment;
step 9: the server generates second vector data from the first set of neighbor nodes and the second set of neighbor nodes, the probing node moves to a second desired location D based on the second vector data,
，/>
is a weighted vector in the second vector data, wherein,
In the present invention, the water area data is lake surface height or tidal reconciliation constant.
In the invention, a first neighbor node set and a second neighbor node set are used as detection nodes and communicate with a radius R in different periods 0 And other probe nodes.
In the invention, the monitoring equipment receives the sensing signal of the detection node and reads the RSSI value W of the sensing signal RSSI =U-T L +gamma, where U is the length of the vertical projection line of the probe node under water, T L For signal transmission loss, gamma is zero-mean Gaussian random noise, according to W RSSI And judging the neighbor nodes, wherein at least one neighbor node forms a first neighbor node set.
In the invention, a detection node j broadcasts an information packet, the information packet records the step number of each hop transmission, after one transmission record, other detection nodes except the detection node j in a water area monitoring area receive the information packet and then send a feedback frame to the detection node j, the detection node j reads the step number of the information packet in the feedback frame, and other detection nodes which accord with the step number of each hop transmission to be 4 steps or less are taken as neighbor nodes, and a second neighbor node set is formed.
In the present invention, the communication radius R 0 The sum of the perceived radii of any two detection nodes with communication conditions is R x Can be moved a certain distance in the vertical direction to a position P 1 A perceived radius of R y Can be moved in the vertical direction by a certain distance to a position P 2 ，P 1 And P 2 Is R es If R is x +R y ≤R 0 And the detection node x and the detection node y are adjacent nodes.
In the invention, in step 7, if the real-time position of any monitoring device is inconsistent with the reference position, the first expected position of the monitoring device is the reference position, and the first vector data is the distance vector from the real-time position to the reference position; if the real-time position of any monitoring device is consistent with the reference position, the first expected position of the monitoring device is the real-time position, and the first vector data is 0.
In the invention, in step 9, if the number of neighbor nodes of any one of the detection nodes changes, the second expected position of the detection node is the critical position where the perceived radius can cover all the neighbor nodes, and the second vector data is the weighted sum of the virtual distances of the detection node relative to all the neighbor nodes; if the number of neighbor nodes of any one detection node is unchanged, the second expected position of the detection node is a reference position, and the second vector data is 0.
In the present invention, the virtual distance is a weighted sum of distance vectors for the probe node to move from any one location to another.
In the invention, under a first monitoring state, a detection node reads water area data in an activated state and reports the water area data to monitoring equipment; and in the second monitoring state, the detection node reads the water area data in the semi-sleep and semi-activation state and reports the water area data to the monitoring equipment.
The deployment optimization method for the monitoring network of the variable water area has the following beneficial effects: the optimal coverage state of the water area mobile monitoring network is recovered by the self-moving mode of the detection node and the monitoring equipment, so that the problem of energy loss aggravation caused by the water area mobile monitoring network, the water flow mobile monitoring equipment and the detection node is avoided. In addition, the detection nodes can be self-adaptively adjusted according to the state of the water area, the purpose of energy conservation and optimization is achieved by reducing the detection frequency and increasing the number of the detection dormant nodes, the problem of energy hollowness of the monitoring network nodes of the variable water area is effectively solved, and the overall energy loss of the monitoring system is reduced.
Drawings
FIG. 1 is a graph of tidal height versus water flow rate;
FIG. 2 is a schematic view of an underwater node arrangement of the deployment optimization method of the monitoring network for variable waters of the present invention;
FIG. 3 is a flow chart of a deployment optimization method of the present invention for a variable water area monitoring network;
FIG. 4 is a partial hardware block diagram of a deployment optimization method for a variable water area monitoring network of the present invention;
FIG. 5 is a schematic diagram of a communication coverage area when a distance between a detecting node i and a detecting node j in second vector data generation and calculation is 2r according to the present invention;
FIG. 6 is a diagram showing the distance between the probe node i and the probe node j in the second vector data generation and calculation according to the present invention
Schematic diagram of the time communication coverage area;
fig. 7 is a schematic diagram of a delay transceiving method according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.
Referring to fig. 1, tidal height is related to water flow rate, with higher tidal heights corresponding to lower water flow rates. When the variable water area monitoring network works, the water area data in the tide state has small change amplitude, the detection nodes are not required to work at high frequency, and the energy-saving effect can be achieved as much as possible by adopting a mode of reducing the detection frequency and increasing the number of the detection dormant nodes. The water area data in the high tide and low tide states have larger change amplitude, the detection nodes are required to keep a high-frequency working state, and the water area data with the best confidence coefficient can be obtained by adopting the modes of increasing the detection frequency and reducing the number of the dormant nodes. In addition, the detection node and the detection equipment move under the influence of the rising and falling tides and the ocean currents, the detection equipment mainly moves in the horizontal direction of the water surface, the detection node mainly moves in the vertical plane direction of the seawater, if the detection equipment and the detection node are regarded as a whole, the detection equipment and the detection node move to change the coverage state of the monitoring network of the whole variable water area, the communication between the detection node and the detection node needs to carry out multi-hop transmission due to the increase of the communication distance, and the energy loss of the whole tide transmission network is increased. Because the movement of the rising and falling tide and ocean current to the variable water area monitoring network nodes is generated, under the condition that the distribution of the sensing network nodes is uneven and unreasonable, a part of edge nodes and the sensing network communication need larger energy, and the problem of energy cavity of the edge nodes can be caused for a long time, so that the service life of the variable water area monitoring network is further attenuated.
Example 1
The deployment optimization method for the monitoring network of the variable water area is used for solving the problems, the coverage rate of the sensing network is improved in a self-moving mode of the detection nodes and the monitoring equipment, and the working conditions of the detection nodes are adjusted according to different tide states. Referring to fig. 2 and 3, the deployment optimization method of the variable water area monitoring network in the present embodiment includes the following steps:
step 1: a plurality of monitoring devices are arranged in the water surface monitoring area, and any one monitoring device is connected with only one underwater detection node through a hard communication cable. The detection node on the hard communication cable can only move up and down, and the monitoring equipment can move left and right through the driving equipment.
Step 2: the monitoring equipment broadcasts a first sensing signal, the detecting node senses information of surrounding neighbor nodes, a first neighbor node set is generated, and the information is reported to the server through the monitoring equipment. After receiving the first sensing signal, the detecting node sends a request frame to the surrounding detecting node, if the response frame of the surrounding detecting node is received, the two detecting nodes are neighboring nodes, and any detecting node stores authentication information of a plurality of neighboring nodes. Authentication information of a plurality of neighbor nodes of the plurality of probe nodes constitutes a first set of neighbor nodes.
In this embodiment, the monitoring device receives a sensing signal of the detection node and reads an RSSI value W of the sensing signal RSSI =U-T L +gamma, where U is the length of the vertical projection line of the probe node under water, T L For signal transmission loss, gamma is zero-mean Gaussian random noise, according to W RSSI And judging the neighbor nodes, wherein at least one neighbor node forms a first neighbor node set. The detection node j broadcasts an information packet, the information packet records the step number of each hop of transmission, one step is recorded through one transmission, other detection nodes except the detection node j in the water area monitoring area receive the information packet and then send a feedback frame to the detection node j, the detection node j reads the step number of the information packet in the feedback frame, and other detection nodes which accord with the step number of each hop of transmission to be 4 steps or less are used as neighbor nodes, and a second neighbor node set is formed.
Step 3: the server broadcasts a first detection signal, the monitoring equipment reports position information, and the server generates a reference position set based on the reference position reported by the monitoring equipment. The reference position is a two-dimensional coordinate on the water surface. Any monitoring device records a reference position, and a server reads the reference positions of a plurality of monitoring devices to generate a reference position set.
Step 4: in a monitoring period, the monitoring equipment periodically acquires water area data m i I=1, 2,3 … n, wherein the water area data is the average water surface height. In this embodiment, the detecting node monitors the current water level and sends the current water level to the monitoring device, and the monitoring device calculates the water level data transmitted by the plurality of detecting nodes at any time point to obtain the average water level. The average water surface height acquired at a plurality of sampling time points forms a water area data set M= { M in one monitoring period 1 ,m 2 ,m 3 …m i }。
The water area data in the narrow sense includes at least tidal volume constant, average water level, and depth reference plane, and the water area data in the broad sense includes at least oxygen content water temperature and microorganism type, and the water area data in the narrow sense is the water area data in the present embodiment. The variable water area monitoring network is a distributed network formed by water surfaces and underwater sensor network nodes through sensor network nodes. The underwater sensor network node is a detection node, and an Ad-Hoc network is formed between the underwater sensor network node and other detection nodes. The water surface sensor network node is monitoring equipment, the monitoring equipment is connected with the detection node through a hard communication cable, the detection node can be fixed, and at least one communication link is arranged between the detection node and the monitoring equipment.
Step 5: the monitoring device calculates the water area variation based on the water area data set M
=m i -m 1 。
During the climax period, the average level increases with time; during low tide periods, the average level height decreases with increasing time; during the tide period, the average level is not affected by time. In this embodiment, considering that the water area data still changes in the tide period, the absolute value of the water area change floating number in one sampling period is recorded as
(upper and lower limits of normal change of water area data), if +.>
Or->
The detection node enters a first monitoring state, if +.>
The probing node enters a second monitoring state.
In this embodiment, in the first monitoring state, the detection node reads the water area data in the activated state and reports the water area data to the monitoring device. The detection node working voltage in the active state is unchanged, and the communication response time is 0.3ms. And in the second monitoring state, the detection node reads the water area data in the semi-sleep and semi-activation state and reports the water area data to the monitoring equipment. The working voltage of the detection node is unchanged in the semi-dormancy and semi-activation state, and the communication response time is 5ms.
Step 6: the server broadcasts a second detection signal, the monitoring equipment reports the position information, and the server generates a real-time position set based on the real-time position reported by the monitoring equipment. The real-time position is a two-dimensional coordinate on the water surface. Any monitoring device records a real-time position, and a server reads the real-time positions of a plurality of monitoring devices to generate a real-time position set.
Step 7: the server generates first vector data according to the real-time position set and the reference position set, and the monitoring device moves to a first expected position based on the first vector data. If the real-time position of any monitoring device is inconsistent with the reference position, the first expected position of the monitoring device is the reference position, and the first vector data is a distance vector from the real-time position to the reference position; if the real-time position of any monitoring device is consistent with the reference position, the first expected position of the monitoring device is the real-time position, and the first vector data is 0.
Step 8: the monitoring equipment broadcasts a second sensing signal, and the detecting node senses the information of the peripheral neighbor nodes, generates a second neighbor node set and reports the second neighbor node set to the server. After receiving the second sensing signal, the detecting node sends a request frame to the surrounding detecting node, if the response frame of the surrounding detecting node is received, the two detecting nodes are neighboring nodes, and any detecting node stores authentication information of a plurality of neighboring nodes. Authentication information of a plurality of neighbor nodes of the plurality of probe nodes constitutes a first set of neighbor nodes.
Step 9: the server generates second vector data according to the first neighbor node set and the second neighbor node set, and the detection node moves to a second expected position based on the second vector data. If the number of neighbor nodes of any one detection node changes, the second expected position of the detection node is a critical position where the sensing radius can cover all neighbor nodes, the second vector data is a weighted sum of virtual distances of the detection node relative to all neighbor nodes, and the virtual distances are weighted sums of distance vectors of the detection node moving from any one position to another position. If the number of neighbor nodes of any one detection node is unchanged, the second expected position of the detection node is a reference position, and the second vector data is 0.
Example two
A block diagram of a deployment optimization method for implementing a variable water area monitoring network of the present invention is shown with reference to fig. 4. The monitoring network comprises: detecting node, monitoring equipment,The server and the communication cable are used for monitoring water area data, communicating with the monitoring equipment and detecting the communication radius R of the node 0 Above the perceived radius, there is at least one communication link between any monitoring device and the probing node. The monitoring equipment can move on the water surface, control the data receiving and transmitting of the detection node and keep communication with the server. And the server sends out a detection signal, and the monitoring equipment and the detection node are called to form a sensing network to monitor water area data. The hard communication cable is one of communication links between the detection node and the monitoring device, and controls the movement of the detection node. Wherein the monitoring device comprises: battery unit, monitoring unit, drive unit. The battery unit is used for supplying power to the monitoring equipment. The monitoring unit is used for controlling data receiving and transmitting of the detection node and keeping communication with the server; the drive unit is used for monitoring the movement of the device.
In this embodiment, the monitoring device is a water surface tide monitoring buoy, the monitoring devices on the water surface are densely deployed, data are transmitted to the sink node through the Ad-Hoc network, the sink node is a relay device lifted in all the monitoring devices, the sink node can store the data in a short time, and after the data packet is transmitted as the relay device, the data packet is erased and the memory is initialized through the built-in Flash memory. The water surface monitoring device can perform irregular movement on a plane. The detection nodes are wireless monitoring sensors for average water surface height, are densely deployed under the sea, have the working voltage of 5V and can keep the communication response time of 0.3ms-5 s. The detection node carries out two-way communication with the monitoring equipment through a hard communication cable, and the communication cable is the hard communication cable and can not generate larger change and fluctuation due to the influence of external factors and is used as a communication link of at least one detection node. And the Ad-Hoc network is formed among the detection nodes.
Example III
The detection nodes disposed in the water surface monitoring area should meet the maximum communication coverage, and in this embodiment, the second vector data generating and calculating method suitable for the present invention is described in detail.
The resultant force applied by the detection node i at the current arrangement position is
，/>
The magnitude and direction of the resultant force of the force with other forces in the undersea environment. The force of the detection node i on another adjacent detection node j in the area is of the magnitude +.>
The magnitude of the acting force generated by the ocean current and the surrounding environment on the detection node i is +.>
Resultant force->
. Then the force between probe node i and probe node j should be of the magnitude: when l ij ＞l t When (I)>
The method comprises the steps of carrying out a first treatment on the surface of the When l ij =l t When (I)>
The method comprises the steps of carrying out a first treatment on the surface of the When l ij ＜l t When (I)>
. Wherein l ij To the Euclidean distance between the detection node i and the detection node j, l t For the optimal distance N between the probing node i and the probing node j, manually set, +.>
For the azimuth angle of the connection line between the detection node i and the detection node j and the horizontal plane, < + >>
For detecting the resultant force to which node i is subjected +.>
Parameter value of>
For detecting the resultant force to which the node j is subjected>
Is used for the parameter values of (a). If the deployment distance between the detection node i and the detection node j is too short, the distance between the detection nodes is smaller than the optimal distance N, and then the resultant force between the detection node i and the detection node j is repulsive force; if the deployment distance between the detection node i and the detection node j is too far, and the distance between the detection nodes is larger than the optimal arrangement condition, the resultant force between the detection node i and the detection node j is the attraction force. And the result obtained through repeated iterative calculation is used as second vector data of the movement of the detection nodes according to the magnitude and the direction of the resultant force born by each detection node.
Referring to fig. 5, when the optimal distance N between the detection node i and the detection node j is 2r, the sensing area of the detection node i and the detection node j at this time reaches the maximum utilization rate, but the partial area does not achieve complete coverage, and the utilization rate of the sensing network in the coverage state is not high. In the present embodiment, referring to fig. 6, the optimal distance N between the probe node i and the probe node j is set to be
Thereby achieving the best coverage, the best distance N under the best arrangement condition satisfies +.>
＜N≤2r。
Example IV
In the tide state, the detection node of the embodiment works in the second monitoring state, and the detection node and the monitoring equipment of the variable water area monitoring network can realize the optimization of network coverage through movement. In this process, the probe node still needs to transmit and receive data, but the urgency of data transmission and reception is not high. Therefore, in the tide state, when the detection node is currently at a position unfavorable for data transmission and reception, the delay waiting stage is started, and when the detection node and the monitoring equipment are both moved to the position favorable for receipt transmission and reception by the detection node, data transmission and reception are performed again according to fig. 7. The present embodiment details a delay transceiving method applicable to the present invention, for further reducing loss of a probing node in a climax period, wherein ACK is a reception acknowledgement.
A plurality of detection nodes in the first neighbor node set are communicated with only one sink node gamma in the sensor network, and the plurality of detection nodes form an effective node set N 0 Active node set N 0 At any time, at least one sink node gamma is connected with the effective node set N at the time 0 Any one of the probing nodes communicates. The delay receiving and transmitting method comprises the following steps:
step 11: the sink node gamma periodically broadcasts beacon information to ensure an effective node set N 0 All the detection nodes in the network can receive the beacon message;
step 12: active node set N 0 Detection node i in (1) 0 Signal strength M based on the beacon message i Calculating the distance between the beacon message and the sink node gamma, and obtaining the beacon message in the effective node set N 0 The probability of success of the transmission in (a);
step 13: if the probability of successful transmission is less than 80%, entering step 14; otherwise, go to step 15;
step 14: detection node i 0 Encapsulating the data as a new message and receiving an active set of nodes N as next hop nodes 0 The message sent by other detection nodes until the transmission success probability is more than 80%;
step 15: and regulating data after the next hop node is sent from the queue, reinserting the copy information rho, and sending the new message to the sink node.
In the present embodiment, in two communication periods T 1 And T is 2 In the case of the real-time signal strength V > R 0 Communication period T 2 Probability of inner transmission success P T2 =(1-α)P T1 +α(R 0 V); if the real-time signal strength V is less than or equal to R 0 Communication period T 2 Probability of success of internal transmission P T2 =(1-α)P T1 +α, where v=10 -B ，P T1 For the probability of transmission success in the communication period T1, R 0 For the communication radius, alpha is a constant value, and 0 < alpha < 1,b is the signal strength of the beacon message.
In the present embodiment, in two communication periods T 1 And T is 2 In this, a beacon message is transmitted from the sink node gamma to the probe node i 0 The beacon message is also sent to the active node set N 0 The other g detecting nodes in the list, the messages received by the g detecting nodes are duplicate messages, and the duplicate efficiency is transmitted to the probability P of success g =1-(1-P T2 ) g Setting a desired probability P f (P f =0.8 or 0.9), the duplicate information ρ of the adjustment data reinserted in step 15 is two cases, if P g ＜P f Then ρ=log1-P g (1-P f ) The method comprises the steps of carrying out a first treatment on the surface of the If P g ≥P f ρ=1. Therefore, when the sink node gamma is distant from the probe node i 0 Is too far apart, has poor transmission success rate, and has more copy information transmitted to the active node set N which does not receive the message 0 The other nodes in the network can be considered to have poorer network environment, and the detection node i required for transmitting the same amount of data information is considered to be required 0 Consuming more energy. So the node i is probed 0 And packaging the data into a new message until the monitoring equipment moves to a first expected position, the detection node moves to a second expected position, the standard that the transmission success probability is more than 80% is achieved, and the lost copy information rho is reinserted.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.
Claims (10)
1. A deployment optimization method for a monitoring network of a variable water area, comprising the steps of:
step 1: arranging a plurality of monitoring devices in a water area monitoring area, wherein any one monitoring device is connected with only one underwater detection node through a communication cable;
step 2: the monitoring equipment broadcasts a first sensing signal, and the detecting node senses the information of the peripheral neighbor nodes, generates a first neighbor node set and reports the first neighbor node set to the server through the monitoring equipment;
step 3: the server broadcasts a first detection signal, the monitoring equipment reports position information, and the server generates a reference position set based on the reference position reported by the monitoring equipment;
step 4: in a monitoring period, the monitoring equipment periodically acquires water area data m i I=1, 2,3 …, and generates a water area data set m= { M 1 ,m 2 ,m 3 …m i }；
Step 5: the monitoring device calculates the water area variation based on the water area data set M
=m i -m 1 If->
Or (b)
The detection node enters a first monitoring state, if +.>
The detection node enters a second monitoring state, wherein +_>
The absolute value of the floating number is changed for the water area;
step 6: the server broadcasts a second detection signal, the monitoring equipment reports position information, and the server generates a real-time position set based on the real-time position reported by the monitoring equipment;
step 7: the server generates first vector data according to the real-time position set and the reference position set, and the monitoring equipment moves to a first expected position based on the first vector data;
step 8: the monitoring equipment broadcasts a second sensing signal, and the detecting node senses the information of the peripheral neighbor nodes, generates a second neighbor node set and reports the second neighbor node set to the server through the monitoring equipment;
step 9: the server according to the first neighborThe set of nodes and the second set of neighboring nodes generate second vector data, the probing node moves to a second desired location D based on the second vector data,
，/>
is a weighted vector in the second vector data, wherein,
2. A deployment optimization method for a variable water area monitoring network according to claim 1, wherein the water area data is lake level or tidal tempering constant.
3. A deployment optimization method for a variable water area monitoring network according to claim 1, wherein the first set of neighbor nodes and the second set of neighbor nodes are probe nodes and communication radius R in different periods 0 And other probe nodes.
4. A deployment optimization method for a variable water area monitoring network according to claim 3, wherein a monitoring device receives a sensing signal of a detection node and reads an RSSI value W of the sensing signal RSSI =U-T L +gamma, where U is the length of the vertical projection line of the probe node under water, T L For signal transmission loss, gamma is zero-mean Gaussian random noise, according to W RSSI And judging the neighbor nodes, wherein at least one neighbor node forms a first neighbor node set.
5. A deployment optimizing method for a variable water area monitoring network according to claim 3, wherein the detecting node j broadcasts a packet, the packet records the number of steps of each hop transmission, one step is recorded through one transmission, other detecting nodes except the detecting node j in the water area monitoring area receive the packet and send a feedback frame to the detecting node j, the detecting node j reads the number of steps of the packet in the feedback frame, and other detecting nodes which meet the number of steps of each hop transmission of 4 steps or less are used as neighbor nodes, and a second neighbor node set is formed.
6. A deployment optimization method for a variable water area monitoring network according to claim 3, characterized in that the communication radius R 0 The sum of the perceived radii of any two detection nodes with communication conditions is R x Can be moved a certain distance in the vertical direction to a position P 1 A perceived radius of R y Can be moved in the vertical direction by a certain distance to a position P 2 ，P 1 And P 2 Is R es If R is x +R y ≤R 0 And the detection node x and the detection node y are adjacent nodes.
7. The deployment optimization method for a monitoring network of a variable water area according to claim 1, wherein in step 7, if the real-time position of any one of the monitoring devices is inconsistent with the reference position, the first expected position of the monitoring device is the reference position, and the first vector data is a distance vector from the real-time position to the reference position; if the real-time position of any monitoring device is consistent with the reference position, the first expected position of the monitoring device is the real-time position, and the first vector data is 0.
8. The deployment optimization method for a monitoring network of a variable water area according to claim 1, wherein in step 9, if the number of neighboring nodes of any one of the probe nodes changes, the second desired position of the probe node is a critical position where the perceived radius can cover all neighboring nodes, and the second vector data is a weighted sum of virtual distances of the probe node with respect to all neighboring nodes thereof; if the number of neighbor nodes of any one detection node is unchanged, the second expected position of the detection node is a reference position, and the second vector data is 0.
9. A deployment optimization method for a variable water area monitoring network according to claim 6, wherein the virtual distance is a weighted sum of distance vectors of the probe node moving from one location to another.
10. The deployment optimization method for a variable water area monitoring network of claim 1, wherein in a first monitoring state, the detection node reads water area data in a normal operating state and reports the water area data to the monitoring device; and in the second monitoring state, the detection node reads the water area data in the semi-sleep and semi-working state and reports the water area data to the monitoring equipment.
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